RandomChoice¶
Draw a random subset from the set of integers from 0 to a given total minus 1, without replacement.
This can then be used as an index set to select from some data. This is similar to first generating a permutation of the integers and then taking the first n elements of that permutation. For drawing with replacement, see the Random Integers node. If deterministic results are sought, pass in a seed; see also CreateRandomSeed for documentation on how seeds are best managed. The node supports alternative compute backends, which can be used to speed up processing. Version 0.8.0
Ports/Properties¶
array¶
Output array.
like¶
Optional template array.
seed¶
Random seed for deterministic results.
shape¶
Shape of the array. Can be omitted if a template array is provided.
total¶
Total number of elements from which the subset is taken.
backend¶
Optional compute backend to use. Keep is the current default, which resolves to that of the template array if one is provided and otherwise numpy unless overridden. Numpy is the standard CPU backend that underpins most of NeuroPype's operations. The others require one or more GPUs to be present on the system, except for torch-cpu. For best performance, keep all arrays that interact with each other (via processing nodes) on the same backend.
precision¶
Numeric precision to use. Keep resolves to the precision of the template array if one is provided, and otherwise to the current default (usually 64-bit). Can be reduced to save memory (e.g. if running on GPU).
set_breakpoint¶
Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.
metadata¶
User-definable meta-data associated with the node. Usually reserved for technical purposes.